Multimodal Clinical Monitoring in the Emergency Department (MC-MED)
收藏DataCite Commons2025-09-25 更新2025-04-16 收录
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https://physionet.org/content/mc-med/
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资源简介:
Emergency department (ED) patients often present with undiagnosed complaints,
and can exhibit rapidly evolving physiology. Therefore, data from continuous
physiologic monitoring, in addition to the electronic health record, is
essential to understand the acute course of illness and responses to
interventions. The complexity of ED care and the large amount of unstructured
multimodal data it produces has limited the accessibility of detailed ED data
for research. We release Multimodal Clinical Monitoring in the Emergency
Department (MC-MED), a comprehensive, multimodal, and de-identified clinical
and physiological dataset. MC-MED includes 118,385 adult ED visits to an
academic medical center from 2020 to 2022. Data include continuously monitored
vital signs, physiologic waveforms (electrocardiogram, photoplethysmogram,
respiration), patient demographics, medical histories, orders, medication
administrations, laboratory and imaging results, and visit outcomes. MC-MED is
the first dataset to combine detailed physiologic monitoring with clinical
events and outcomes for a large, diverse ED population.
急诊科室(Emergency Department,ED)患者常以未确诊的主诉就诊,且生理状态可快速演变。因此,除电子健康档案(electronic health record)外,持续生理监测数据对于明晰疾病的急性病程及干预应答情况至关重要。急诊诊疗的复杂性及其产生的大量非结构化多模态数据,限制了详细急诊数据的科研可及性。
我们发布了急诊多模态临床监测数据集(Multimodal Clinical Monitoring in the Emergency Department,MC-MED),这是一套全面的多模态去标识化(de-identified)临床与生理数据集。MC-MED涵盖2020年至2022年间某学术医疗中心的118,385例成人急诊就诊病例。数据集包含持续监测的生命体征(vital signs)、生理波形(physiologic waveforms),其中包括心电图(electrocardiogram)、光电容积描记图(photoplethysmogram)及呼吸波形(respiration),此外还涵盖患者人口统计学信息、病史、医疗医嘱(orders)、给药记录(medication administrations)、实验室与影像学检查结果,以及就诊结局。MC-MED是首个针对大型多样化急诊人群,将详细生理监测数据与临床事件及就诊结局相结合的数据集。
提供机构:
PhysioNet
创建时间:
2025-01-15
搜集汇总
数据集介绍

背景与挑战
背景概述
MC-MED是一个全面的急诊科多模态临床数据集,包含118,385名成年患者的连续生理监测和临床记录,首次结合了生理波形和临床事件数据,适用于急诊医学的多样化研究。
以上内容由遇见数据集搜集并总结生成



